Conversable Economist

It may seem obvious that health insurance helps health, but very few cause-and-effect conclusions are obvious to economists. For example, suppose that we just compared the health of everyone who has health insurance and everyone who doesn’t. It would be unsurprising to find that those with health insurance are healthier, but the two groups will also differ in many other ways. For example, given that many Americans get health insurance through their employer, the chances are good that those with health insurance are more likely to be employed and on average to have higher incomes. How can we disentangle effect of health insurance from other possible confounding factors?

Or imagine that you compared the health of people before-and-after they had health insurance. This approach has some promise, but again, if getting health insurance is also connected to getting a job with benefits, a higher income, and perhaps a more settled life in other ways, then the task of separating out the effect of health insurance from other confounding factors remains.

Or one can imagine a social experiment in which a large group is randomly divided, with part of the group receiving health insurance and part not. Then you could track the two randomlly selected groups over time, and see what happens. This is essentially the approach used to test the safety and efficacy of new drugs, for example. Thus, social scientists are on the lookout for situations where this kind of random selection in to health insurance happened, but perhaps by accident rather than policy.

In their essay, “The Impact of Health Insurance on Mortality,” Helen Levy and Thomas C. Buchmueller focus in some of these situations in which access to health insurance was determined in a way with a high degree of randomness (Annual Review of Public Health, April 2025).

One of the most clear-cut examples happened in Oregon in 2008. The state wanted to expand eligibility for Medicaid, but didn’t have the money to expand it for everyone. The result, as the authors describe it was”the 2008 Oregon Health Insurance Experiment, which studied ∼75,000 low-income adults under age 65, 40% of whom were selected by lottery to be eligible for Medicaid (the treatment group) with the remaining 60% serving as a control group.” Thus, some randomly received health insurance, and some did not.

Another truly randomized study looked at an “IRS initiative that sent letters in early 2017 with information about HealthCare.gov to a randomly selected sample of 3.9 million households that had been subject to the ACA [Affordable Care Act] individual mandate penalty for failing to have coverage in the previous year. The study finds that the letters led to a small but significant increase in coverage.” In this case, some randomly received a letter that increased the share of that group with health insurance, while others did not.

Yet another approach looked at those admitted to California hospitals who were either just under age 65, and thus not eligible for Medicare, or just over age 65, and thus covered by Medicare. The idea here is that the just-unders and just-overs should be highly comparable groups: after all, the only way they differ was in being born a few months apart. In this “discontinuity” approach (in this example, the discontinuity is age 65), the greater or lesser share of health insurance across groups is quite similar to random.

Other examples involve Medicaid coverage Medicaid is a joint federal-state program, so the program was often introduce in a staggered way, over time, across states. This was true back in the 1960s, when Medicaid first enacted, and it was also true in the 2010s, when states were allowed to expand Medicaid coverage, but over several years, only some did so. A researcher can look at this data and see if, when a group of people become eligible for Medicaid, the pattern of their health outcomes then shifts from previous patterns–and the patterns of health outcomes for groups that did not become eligible at that time. Here, the random ingredient is the staggered time periods in which health insurance was introduced.

My theme here is that there are plausible ways for researchers to study a cause-and-effect relationship between health insurance and health. Of course, not all of these studies cover the same age groups, or find the same outcomes. But my guess is that a number of readers care less about the way the studies are done, and more about how the authors of this review would summarize the overall results. Here, I quote from the abstract of their paper:

A 2008 review in the Annual Review of Public Health considered the question of whether health insurance improves health. The answer was a cautious yes because few studies provided convincing causal evidence. We revisit this question by focusing on a single outcome: mortality. Because of multiple high-quality studies published since 2008, which exploit new sources of quasi-experimental variation as well as new empirical approaches to evaluating older data, our answer is more definitive. Studies using different data sources and research designs provide credible evidence that health insurance coverage reduces mortality. The effects, which tend to be strongest for adults in middle age or older and for children, are generally evident shortly after coverage gains and grow over time. The evidence now unequivocally supports the conclusion that health insurance improves health.

The US economy has emerged from the pandemic growing at a faster pace than the UK and other high-income countries. Simon Pittaway tackles the question of why in “Yanked away: Accounting for the post-pandemic productivity divergence between Britain and America” (Resolution Foundation, April 2025).

The average standard of living in any economy, over time, will be determined by the productivity of workers in that economy. This figure calculates productivity as GDP/worker, adjusted so that productivity in all the G7 countries just before the pandemic was equal to 100. (The G7 countries are the US, UK, France, Germany, Italy, Japan, and Canada.) You can see the red US line pulling ahead of the rest. The official British data is the dashed line, but Pittaway argues that the official data is too optimistic, and the actual labor productivity in the UK is actually lower than it was in 2019.

When you trace the productivity patterns deeper into the data, what do you find? For the UK, Pittaway points to several industries where the decline in productivity since 2019 has been especially high.

For example, it appears that the UK health care sector is experiencing an outright decline in productivity. In the UK oil and natural gas sector, employment is up slightly, although production of oil is down by two-fifths and production of natural gas is down by three-fifths. There seems to have been a decline British productivity in wholesale and retail trade, as well–that is, output in the industry is down much more than employment. Here, I want to focus on a few bigger-picture issues.

One is the level of investment. Pittaway writes:

The investment gap between Britain and America has widened in recent years. Investment by British businesses hit a brick wall around the time of the Brexit referendum.42 As a result, growth in Britain’s capital stock has slowed by two-thirds, from 2.8 per cent in 2016 to 0.9 per cent in 2023. Notably, this slowdown has been particularly stark in the service sectors where the US has significantly outperformed the UK. In real terms, American businesses in those sectors invested 24 per cent more in 2023 than in 2016, while their British counterparts invested only 7 per cent more.

Back when Brexit was happening, I wrote that, as an American, I understand the urge to break trade ties and declare independence. But whatever the merits of Brexit as a cry for self-determination and national autonomy, it wasn’t good for investment incentives. The current US push to fracture trade ties with the rest of the world, especially as it is happening in unclear and ever-evolving ways, won’t be good for US investment incentives, either.

A second big difference worth noting is the US productivity growth advantage in technology-using jobs. US firms are investing more in technology, in particular. As a result, productivity growth in service-related has been higher in the US economy. Pittaway writes:

Professional services emerge as a particularly important source of productivity growth in the US. In part, this reflects the rapid growth of America’s large, high profile tech companies, who mostly operate in the information and communications sector. But productivity growth in professional services sectors that use rather than produce tech has been more consequential. Between 2019 and 2023, professional, scientific and technical services accounted for one-sixth (17 per cent) of the post-pandemic gap in productivity growth between the US and the UK – twice as much as the tech (ICT) sector (8 per cent). The additional tailwind from faster productivity growth in less glamorous service sectors – like administrative and support services, wholesale and retail, and hospitality – shouldn’t be overlooked. For example, different rates of productivity growth in the wholesale and retail sector account for almost as much of the US-UK aggregate productivity growth gap (0.51 percentage points) as information and communications.

A third difference is that energy costs are much lower in the United States than in the UK, or in other countries across Europe. The left-hand panel compares the price of natural gas; the right-hand panel compares the price of electricity.

Finally, the US economy seems to have emerged from the pandemic with a rise of dynamism: more new companies being started, more economic shifts toward areas of greater economic opportunity. Here’s a figure illustrating one aspect of that pattern. As you can see, company births and deaths in the US spiked during the pandemic, but company births have remained high since then. There’s no such movement in the UK data.

During the pandemic, many European countries focused on preserving the connection between workers and their jobs, while the US focused more on income protection for workers, but without linking that aid to remaining with their previous employer. One consequence of those different policy choices is that the US economy has been more fluid in adjusting since the pandemic.

Fertility rates are falling around the world, but Republic of Korea is the outlier, with a fertility rate of 0.72 in 2024. The International Monetary Fund, in its report on Korea’s economic situation (generally quite good), thought that Korea’s low fertility justified adding an “Annex” to its most recent report on Korea’s economy: “Addressing Korea’s Declining Labor Force” (IMF Country Report No. 25/41, Republic of Korea, 2024 Article IV Consultation, February 5, 2025).

This figure puts Korea’s fertility rate in perspective. You can see that the US fertility rate is a little above the average for the OECD countries (mostly the high-income countries of the world). Countries with low fertility rates include Spain, Italy, and Japan. But even among the nations with low fertility rates, Korea is a clear outlier.

As the report notes: “According to the UN’s population projection, Korea’s population is projected to decline by 17 million (equivalent to 33 percent of its current population) by 2070. The working-age population, which peaked in 2019, is projected to decline to 36.3 million (70.2 percent of total population) in 2024; 34 million (66.4 percent) in 2030; and 16 million (45.8 percent) in 2070. This decline is putting considerable strain on labor supply and hence potential growth of the Korean economy.”

Let me just empahasize that opening line again: with a fertility rate of .72, Korea’s population will fall by one-third in less than a half-century. Setting aside extreme conditions of war, disease, famine, and oppression, I do not know of any country which has gone through such an experience.

To see this another way, the top figure shows Korea’s population by age group in 2023. As you can see, the young age groups are quite small compared to the middle age groups. The bottom figure than projects out these trends to 2070. At that point, the middle age groups are small compared to the elderly. Also, if you look at the figure more closely, you will see that the horizontal axis in 2070 is different from the figure in 2023, so the decline in the size of the bars is even larger than it might at first appear.

Discussions of fertility can have a high emotional charge, because they sometimes can sound as if the policymaker (or the innocent writer) is telling people–and women in particular–how many children they “should” have. It’s a legitimate concern. But choices about children are heavily affected by other factors: cost of housing and schools, flexibility of workplace arrangements, availability of childare, structure of labor force, and more. In Korea, these other factors tend to lean against having children.

Consider some of these factors:

Housing costs. The IMF notes: “As of 2024Q1, it is estimated that median income families spend about 63 percent of household income for loan repayment of a median-priced home. The ratio is notably higher in the Seoul Metropolitan Area (151 percent), where the best jobs and education institutions are concentrated, and for larger living spaces needed to raise a child (153 percent for a property bigger than 135 square meters).” Payment of this size pretty much define “unaffordable.” (For those who don’t read metric, 135 square meter is about 1200 square feet; that is, a typical size for a two-bedroom apartment or condo.)

The centrality of private tutoring for children. Mothers in Korea are often expected to oversea a regime of private tutoring, which is seen as necessary to gain entry to prestigous univerisities. The IMF: “Korea’s high private tutoring participation rates largely reflect fierce competition to enter prestigious universities. … A significant portion of parent’s income is thus spent on private tutoring. In 2023, 78.5 percent of Korean primary and secondary school students took private tutoring (Ministry of Education, 2024). Monthly average expenditure for private tutoring per student relative to household disposable income has increased sharply since 2015, reaching … roughly 10 percent of average household disposable income in 2023. Empirical analysis suggests that prevalence of private tutoring is negatively associated with country-level total fertility rate …”

A dual-structure workforce. Korea’s labor market has what is called a “dual structure,” which means that one set of jobs are highly paid, highly demanding, seniority-based and often quite secure, while the remaining jobs are less well-paid, with limited promotion prospects, and often insecure. Thus, a mother in Korea will have a very hard time remaining on the highly-paid track–and in a dual-structure economy, once you are off the highly-paid track, it is very difficult to re-enter that track. Here’s a figure showing flexibility of working arrangements. The US ranks near the top; Korea is near the bottom.

This figure illustrates the dual labor-market in Korea by showing that temporary and self-employment in Korea are especially high in comparison to other countries.

Although the IMF report doesn’t mention this point, it also seems relevant to me that the tradition in Korea has been for a married couple to move in with the husband’s family, which has often meant that the wife end up doing household tasks with her mother-in-law. This pattern has become less common over time, but the possibility of such a living arrangement seems likely to discourage marriage and child-bearing for at least some women.

The IMF report goes into detail about how various policy steps could offset Korea’s low fertility rates, at least to some extent. I should also add that the dangers of extrapolation apply here with some force: If Korea’s population and workforce decline with the speed of these predictions, then in the next few decades housing should become substantially more affordable, admissions at major Korean universities will be less selective, firms will be under pressure to be more flexible in their workforce, and so on. As the US experienced after World War II, baby booms are possible, too. Decisions about how many children you “want to have” are not made in a vacuum.

US investors put money in assets of other countries, including “portfolio investment” which focuses on ownership of stocks and bonds without a management interest, and “foreign direct investment” which is owning enough of a foreign company to have a management interest. Conversely, foreign investors put money into US dollar assets in the US economy. Erin Whitaker and Tiffany Dang of the US Bureau of Economic Analysis put togethere the most recent data in “A Look at the U.S. International Investment Position: Fourth Quarter and Year 2024” (Survey of Current Business, April 7, 2025).

Here’s the overall picture. Just to be clear, “U.S. Assets” does not mean assets owned by the US government, but instead is the foreign assets owned by all US firms and individuals. Conversely, “U.S. Liabilities” does not mean that this is a debt owed by the US government. Instead, it is the sum of the assets that what foreign investors–private and public–own across the US economy. Also, notice that the vertical axis here is being measured in trillions of dollars: for perspective, total US GDP in 2025 will be about $28 trillion. We are talking about substantial amounts here. The gap between US assets and US liabilities was about $7 trillion back in 2015, but is now about $26 trillion.

Clearly, US liabilities exceed US assets, and the gap is growing. What are the implications of that fact in practice? To get a grip on these issues, first look at a breakdown of these assets and liabilities: first the US ownership of foriegn assets and then the foreign ownership of US assets.

There are several ways that these totals for assets and liabilities can change over time. If the US stock market goes up, for example, then the assets of foreign investors in the US stock market also rise in value. Indeed, the primary reason why “US Liabilities” have risen so sharply, and why the gap between US assets and liabilities has increased so much, is that the US stock market has been rising much faster than foreign stock markets, and the value of holdings of US assets by foreign investors has risen accordingly.

Other factors make a difference as well. All the figures here are expressed in dollars, so in figuring out that the foreign investments of US investors are worth, there has been an exchange rate conversion–and shifts in exchange rates will affect the total US assets.

In some cases, assets owned in another country involve a near-term financial payments; for example, if a foreign investor owns US Treasury bonds, the investor will be paid interest on those bonds. However, if a foreign investor owns stock in a US company that doesn’t pay dividends, the value of that stock can rise and fall without causing a need for a payment to that foreign investor.

I’ll focus here on the returns on direct investments and portfolio investments. As you’ll US investors holding foreign assets have typically earned higher rates of return than foreign investors holding US assets–a situation that the research literature calls “exorbitant privilege.”

Here’s a figure showing the return on direct investments over time, from a different Bureau of Economic Analysis report. The bars show the amounts paid in billions of dollars, as measured on the left-hand axis, while the lines show the rate of return, measured on the right-hand axis. Clearly, what US investors are receiving from direct investments abroad is higher than what foreign investors are receiving.

What about the US return on foreign portfolio investments, and converse, the foreign return on US portfolio investments? Carol C. Bertaut, Stephanie E. Curcuru, Ester Faia, Pierre-Olivier Gourinchas offer new measures of “New Evidence on the US Excess Return on Foreign Portfolios” in a Federal Reserve discussion paper (Number 1398, November 2024). Lookign at data from 2005-2022, they write:

Portfolio returns play an important role in global wealth dynamics. A key stylized fact, first established by Gourinchas and Rey (2007a), is that the return on US external claims consistently exceeds that on US external liabilities, the so-called ‘exorbitant privilege.’ A positive excess return helps to stabilize the US external asset position and makes US current account deficits more sustainable … Our first finding is that the US excess return on portfolio (equity and bond) assets averages a modest 0.5% per year over the full sample. It is significantly higher, averaging 1.7% per year, when we exclude the pandemic period (2020-22).

Looking at the figures above, the foreign portfolio investment in US assets is about $17 trillion higher than US portfolio investment in foreign assets. Using the over-time average of 0.5% per year, US investors would be receiving about $85 billion more each year from their portfolio investments than foreign investors are receiving from their US portfolio investments. If one excludes the pandemic and uses the more common 1.7% difference, the gap in portfolio-related gains would be $289 billion per year.

The fundamental reason why US investors in foreign countries are receiving higher returns is that they are willing to take on more risk. To oversimplify significantly, you can imagine foreign investors putting money into bonds issued by the US Treasury and by big corporation, while US investors are more likely to be seeking out investment with both greater risk and opportunities for growth.

These figures suggest some reorientation of how one thinks about “international trade. As yet another Bureau of Economic Analysis press release reports (February 5, 2025), the US economy had a trade deficit in goods of $1,211 billion in 2024. This number has been the focus of the tariffs that President Trump has announced. However, the US economy runs a trade surplus in trade of services, totalling $293 billion in 2024. (Although the US trade deficit in goods is taken, at least in White House political circles, to be full proof of unfair trade barriers by other countries against US exported goods, the US trade surplus in services, by contrast, has no implications at all as to whether the US is imposing unfair trade barriers in services with regard to US imported goods. Go figure.)

Moreover, payments across borders as a result of direct and portfolio investment also favor the US by several hundred billion dollars. Moreover, I should emphasize that a variety of other payments go into what is called the “current account balance,” the broadest measure that combines international payments related to trade in good and services, as well as foriegn investments, and also includes remittances that immigrants send to their home countries, payments made by foreign insurance companies, payments between governments, and other categories. For those who want the full account of the current account balance, a baseline starting point is “U.S. International Transactions, 4th Quarter and Year 2024.”

How much should Americans worry about the large and growing gap between US assets and US liabilities? Looking back about 20 years, the gap–that is, the “net foreign asset position”–was much smaller: back around 2005, the gap was about 15% of US GDP, while now it’s more than 90% of US GDP. Twenty years ago, the gap was much smaller, so that that when the net foreign asset position became somewhat larger and more negative in a given year, this change was fully offset by the higher returns being earned by US investors holding foreign assets. This was “exorbitant privilege.”

But now, thanks mostly to foreign ownership of US assets and the very strong rise in US stock markets, the net foreign asset position has become enormously more negative at $28 trillion. The rate of return earned by US investors with foreign assets continues to exceed that of foreign investors holding US assets, but that $28 trillion gap is so large that the additional payments received by US investors in a given year no longer cover the increasingly negative net foreign asset position. Thus, Andrew Atkeson, Jonathan Heathcote and Fabrizio Perri have a research paper forthcoming in the American Economic Review called “The End of Privilege: A Reexamination of the Net Foreign Asset Position of the United States.”

As Atkeson, Heathcote, and Perri point out, this fact may alter how you think about the large gains in US stock markets. If US stocks are primarily owned by US citizens, then gains in the US stock market redound to the benefit of Americans. But the rising foreign ownership of US stock markets suggests that gains in US stocks are increasing flowing to foreign investors, instead. International diversification of investments has both gains and tradeoffs.

Tyler Cowen has one of his characteristically wide-ranging “Conversations With Tyler” with “Kenneth Rogoff on Monetary Moves, Fiscal Gambits, and Classical Chess” (April 30, 2025, audio and transcript available). Here, I’ll pass over the comments about the economies of China, Pakistan, Latin America, Japan, the EU, and Argentina, and focus on Rogoff’s comments on the prospects for US debt and for a surge of inflation in the medium-term:

Looking way forward, I would just say we’re on an unsustainable path [for federal givernemtn borrowing]. We will continue to have our debt balloon. Eventually — not necessarily in a planned or coherent way — I think we’re going to have another big inflation soon, next five to seven years, maybe sooner with what’s going on, and that’s going to bring it down just like it did under Biden. It brought the debt down. Then the markets are, fool me once, shame on you. Fool me twice, no, we’re raising the interest rate, and then we’ll have to make choices. …

Last time [during the Biden administration] we probably had a bonus 10 percent inflation over the 2 percent target cumulatively, maybe 12 percent. I think this time, it’ll be more on the order of cumulatively over the 2 percent target, 20 percent, 25 percent. There’s going to be an adjustment. I don’t think the debt is going to be the sole contribution to that. There are many factors. You have to impinge on Federal Reserve independence. Probably, there’ll be some shock, which will justify it. I don’t know how it’s going to play out.

I know that for years, people have said the US debt is unsustainable, but it hasn’t come to roost because we’ve lived through this post-financial crisis, post-pandemic era of very, very low and negative real interest rates. That is not the norm. There’s regression to mean. You know what? It’s happened. Suddenly, the interest payments start piling up. I think they’ve at least doubled over the last few years. They’re quickly on their way to tripling, of going up to $1 trillion. Suddenly, it’s more than our defense spending. That’s the most important macro change in the world, that real interest rates appear to have regressed more towards long-term trend. …

The problem is in our politics. It’s in our DNA. We’re convinced that we’re immortals, and we can just do whatever we want. You go around Washington, whatever they say, I think that’s what they think. Again, this key thing is that real interest rates, the interest rate adjusted for expected inflation — and I’m looking at the long term — they’ve come up. They’re not super high, but they’re more like they were in the early 2000s, and, I think, of reasonable projections, they’re going to stay around the level they are now. …

My students, for a long time, just didn’t believe there’d ever be inflation again. I would teach it; they would fall asleep. I remember asking a question even to someone who was a research assistant at a big central bank, “Explain this to me about inflation.” She said, “My generation doesn’t ever expect to think about inflation. We don’t have it. Please give examples of this.” So no, I would suspect we will have high real interest rate.

In his new book on how to reduce gun violence, Jens Ludwig tells the story of a classic social science Good Samaritan experiment (the book is Uuforgiving Places: The Unexpected Origins of American Gun Violence).

In a canonical study from the 1970s, a team of social psychologists enrolled forty students from the Princeton Theological Seminary and asked them to walk across campus to another university building to deliver a talk on the parable of the Good Samaritan. In the biblical story, a man is robbed and left injured at the side of the road; he is then ignored by a passing priest before being cared for by a passing good Samaritan. In the study, the subjects encountered a person (a plant of the researchers) slumped in a doorway, not moving, eyes closed, who would cough and groan as the subject went by—a person, in other words, in need of help. Yet only 40 percent of the seminary students stopped to help the person in need. As the researchers observed, “On several occasions, a seminary student going to give a talk on the parable of the Good Samaritan literally stepped over the victim as he hurried on his way.”

What distinguished the subjects who helped from those who didn’t? Was it something about their character, like their level of religious devotion? It turns out that how religious subjects were explained little about who stopped to help and who didn’t. The most important factor? Whether the subject was in a hurry. Some were randomly assigned to be told they were late to give their talk, while others weren’t. Those who were in a hurry helped far less (10 percent) than those not in a hurry (63 percent). The lesson of the Bad Samaritan is not so much about the effects of hurrying per se. It’s more general: For helping behavior, the situation mattered far more than the person.

Many of us live large portions of our days in a hurry. But people in a hurry are often distracted, to the extent of not reacting to what’s in front of them in the way that they would actually prefer–that is, if people act (or don’t act) in they way they would have preferred if they weren’t in a hurry. The long-ago famous UCLA basketball coach John Wooden is quoted as saying: “Be quick, but don’t hurry.”

Ludwig’s theme about gun violence is that something like 80% of gun violence is not about immediate financial gain, as in a robbery, nor about psychopaths and assassinations, as in the movies, but instead is about a situation where an argument erupts between two people. Ludwig argues that there is often a short window of time when the argument escalates past a critical point into violence. If we can find ways to make the escalation less likely, or to interrupt that (say) 10-minute window, we can reduce the likelihood of one person dying and another person ending up in prison. The solution is often less about confrontation than it is about distraction–so that people who are walking down a tunnel of rage, or close to doing so, can divert to a different path. Ludwig makes no claim that this is a full or complete solution to gun violence, but only that there is considerable evidence from urban design and violence prevention programs that demonstrate real gains.

Ludwig is of course aware that this prescription won’t satisfy those who think the solution to gun violence involves laws and rules to restrict gun use, nor those who believe that a policy of more severe punishments for shooters will cause people in the midst of white-hot anger to think carefully and back away. He writes: “If, for better or worse, the four hundred million firearms in the US aren’t just going to disappear anytime soon, if major nationwide gun control is unlikely in the foreseeable future, then progress on gun violence can—or maybe must—come from figuring out how to reduce the tendency of people to use those widely available guns to harm one another.”

For some previous posts on the lack of evidence for what policies are likely to reduce gun violence, see here and here. For those who want to know more about the Good Samaritan study, the citation is Darley, John M., and C. Daniel Batson. “‘From Jerusalem to Jericho’: A Study of Situational and Dispositional Variables in Helping Behavior.” Journal of Personality and Social Psychology 27, no. 1 (1973): 100–108.

If you are looking for a fairly easy read that describes how economists view the effects of tariffs, you could do worse thatn start with tbhe overview essay by Kyle Pomerleau and Erica York, “Understanding the Effects of Tariffs” (American Enterprise Institute, April 2025). Here, I’ll skip past their historical discussions of US tariffs, and President Trump’s historical affinity for tariffs, and just summarize some bottom lines–with more details available in the paper itself:

Will tariffs reduce the US trade deficit?

Although it may seem intuitive that taxing imports would reduce net imports, tariffs do not have a direct impact on the balance of trade. The trade balance is driven by net lending and borrowing between the United States and the rest of the world. Instead of reducing net imports, tariffs simply reduce overall trade. … Tariffs cannot permanently change the trade balance. Tariffs that reduce imports result in an equivalent reduction in exports in present discounted value, reducing overall trade but not the trade deficit.

How will tariffs affect the US dollar exchange rate?

Tariffs have a direct impact on the value of the USD [US dollar] by changing its supply (or the demand for foreign currency). When a tariff is enacted, it results in reduced US demand for imported goods. Since foreign exporters receive dollars for goods sold to Americans, a reduction in US demand for imported goods would reduce the supply of USD in the world market, resulting in an appreciation of the USD relative to other currencies. … [T]he stronger dollar would have an immediate negative impact on exports. Foreigners would find it more expensive to purchase US goods and services because foreigners earn incomes in their domestic currency and need to convert it to the more expensive USD to purchase US goods. … Finally, the appreciation of the USD due to enactment of a tariff would result in a onetime transfer of wealth from Americans to foreigners. A onetime appreciation of the USD would mean that the USD value of foreign assets would fall because it would become more expensive to convert foreign currencies into USD. At the same time, the stronger USD would be more favorable to foreigners, who could now receive a higher return in their domestic currency for a fixed amount of wealth denominated in USD.

How will tariffs affect the price level, and thus affect the real value of wages?

Intuition suggests that tariffs, like other excise taxes on products, should raise prices. While such taxes may raise the price of the taxed goods, the general price level is ultimately determined by the Federal Reserve’s actions. The Federal Reserve, which has a mandate for both price stability and employment, would likely increase the
price level in response to tariffs, but only if the tariff increase were significant. … Note that accommodation by the Federal Reserve results in a onetime adjustment to the price level, not a persistent increase in the rate of inflation. It is worth emphasizing that whether the Federal Reserve accommodates the tariff, it burdens households in the form of lower real, after-tax income. With accommodation, nominal incomes remain fixed while nominal prices rise, resulting in falling real incomes. Without accommodation, nominal incomes fall while nominal prices remain fixed, also resulting in falling real incomes.

Tariffs and the likelihood of retaliation

Trade is a two-sided transaction that benefits both buyers and sellers. The taxes that the United States imposes on foreign goods have a negative impact on the US economy and its trading partners’ economies. Likewise, the taxes foreign countries place on US exports harm both the foreign country imposing the tariffs and the United States. A foreign tariff can reduce demand in a foreign jurisdiction for US goods, reducing income earned by affected US exporters. … In 2018 and 2019, jurisdictions including China, the European Union, Japan, Russia, and the United Kingdom responded to US tariffs by imposing tariffs on US exports, affecting approximately 8.7 percent of 2017 exports (Williams and Hammond 2020). The US Department of Agriculture estimated that in 2018 and 2019, direct US agricultural export losses totaled more than $27 billion (Morgan et al. 2022). Retaliation created an additional drag on US output in the manufacturing sector, which, combined with the effects of higher input costs from tariffs, offset the benefits of protection for the sector (Flaaen and Pierce 2024).

A 10% tariff on goods might plausibly raise about $200 billion per year in tax revenue for the government. For comparison, federal revenue from the individual income tax is more than 10 times as high, at about $2.3 trillion per year.

Consider a proposal to enact a 10 percent across-the-board tariff on imported goods. Actual goods imports totaled $3.3 trillion in 2024 (BEA n.d.) … The taxable base would be smaller after considering noncompliance and behavioral responses. We assume noncompliance of 15 percent, which is consistent with the average across all taxes and the noncompliance rate assumed by the Tax Policy Center when it estimates the revenue effects of a value-added tax (Toder et al. 2011). In addition, we assume an elasticity of −0.76 in the first year that grows to −2 by 2032. … Applying the Joint Committee on Taxation’s latest income and payroll tax offset, which suggests that 26.2 percent of gross tariff revenue over the next decade will be offset through reductions in income and payroll taxes, the 10 percent across-the-board tariff is projected to raise $1.95 trillion over the next decade on a conventional basis …

Pomerleau and York are almost visibly striving for an even-handed tone, which of course endears them to me. But I’ll note that as a result they do not emphasize what seem to me some of the ways in which tariffs can severely injure US manufacturing firms: by taxing the imported inputs that US manufacturing firms need for production, and by the likelihood that US manufacturing firms will lose export markets as other countries retaliate with tariffs of their own.

Jon Hartley serves as interlocutor in “Revisiting Empirical Macroeconomics with Robert Barro” (Hoover Institution, Capitalism and Freedom Podcast, March 25, 2025, audio and transcript available). Here are a few of the comments from Barro that especially caught my eye.

One basic question in economics is about “the multiplier”–that is, how much will an increase in government spending boost the size of the economy. If the boost in government spending doesn’t increase the size of the economy, the multiplier is zero. If it raises the size of the economy one-for-one, then the multiplier is one. Optimists about governmetn spending sometimes claim the multipler is more than one, while pessimists hold that it might be negative. Barro argues that, at least in most settings, the evidence supports a multiplier between zero and one. Barro says:

Looking at the variations in military spending in the US context over a fairly long time period is a very good setting for trying to isolate spending multipliers associated with basically exogenous movements in the amount of government expenditure. You wouldn’t do this for many countries during wartime because the direct destructive effects of wartime tend to be dominant. And typically in wartime you would estimate negative spending multipliers associated with military outlays. But the US is different in that respect. It doesn’t have that kind of massive destruction associated, particularly with World War II.

So it was a very good setting, I think, for looking to isolate the effect of these exogenous and large spending changes. So the multipliers were positive. I mean, the right baseline is 0, not 1. If the multiplier is 1, it means you’re basically getting as much output as you’re using up, which makes it sound like it’s a free thing … But the right benchmark is a multiplier of zero because that means that in order to get the extra spending let’s say for military, you have to cut back on other spending one for one. …

So we found multipliers that were more like a half or something, which means that you have to pay for 50% of the extra. So it’s a multiplier of one and above is kind of completely ridiculous. I mean, a multiplier above one means you’re not only getting the military spending for free, you’re getting something extra for coming from nowhere. It should be a very surprising result to have multipliers that are above one. And you certainly wouldn’t find that in normal times or in some kind of long run setting. 

Inflation reduces the value of existing debt. Thus, if government spending leads to an increase in inflation–and thus reduces the value of existing government debt–there is a sense in which the government used inflation to “pay for” its spending increase. Here’s Barro:

So if you have a massive increase [in government spending], such as the transfer payments, even more under Biden than under the first Trump administration, a way to avoid paying for that by cutting other spending or by raising taxes is by having a inflation that’s surprising from a perspective of a pre crisis period. And that basically wipes out a lot of real value of the government bonds that are outstanding and it amounts to a very large temporary source of revenue which can be something like 10, 15% of the GDP. So it’s not a minor deal. And that’s empirically about what happened in the US and also in other places. …

[P]eople don’t like the idea that it might not have been completely crazy to pay for the expenditure in substantial part through this surprise inflation. I get a lot of grief on that point from people who normally, who normally are on my side about things because they just want to think of the inflation as being stupid and being dramatically harmful. So I think what was harmful is the excessive fiscal expansion, particularly under Biden. It was unnecessary to have that vast increase in transfer payments, but given that you had it, we effectively paid for most of it through the surprise inflation. And maybe that part was not so crazy because the alternatives would have been also very costly.

Back in the 20th century, it was common to study causes of economic growth by looking a patterns across countries. However, these studies were inevitably about correlations, not necessarily causation. Thus, a lot of economic research has now shifted to looking for experiments–either designed or “natural” in some way–where causation is more clear. Barro argues that for broad topics of economic growth, cross-country regressions should continue to be viewed as a productive approach.

if you want to think about what matters for growth and, and how it depends on policies and things like property rights and fertility behavior and education and all those, the natural empirical arena to consider there is the cross country experiences where you have a lot of variety in terms of different policies and institutions being put into place and you have some hope from that of trying to isolate what things matter for long run economic growth. And that was the work I particularly put my efforts into in the 1990s going into the 2000s. And for a while there was a tremendous interest in that work and it was probably the most cited part of economics overall. But then you had this kind of so called credibility revolution in econometrics and identification and it was clear that to be using this cross country context leads to a lot of issues where you don’t get perfect identification.

There are some legitimate problems that arise in terms of various things being endogenous and too many things potentially mattering. But then I don’t understand how the outcome from that is supposed to be. Then you ignore the best data that you have that pertain to these questions. What which is this cross country experience, you almost never have experiences in terms of macroeconomics and growth where you have the kinds of exogenous experiments or near experiments that you would want to get clean identification. And then I think it’s really unfortunate that what can be gleaned from the data that are available with the possible identification methods and implementations and then ignoring that I think is a great mistake. But that’s the situation we’re in now. It’s basically you just can’t do that kind of work now. It’s viewed as not legitimate. And I think that that’s really wrong and unfortunate.

In its most recent World Economic Outlook report, the IMF includes a chapter on “The Rise of the Silver Economy: Global Implications of Population Aging” (April 2025).

Here are the big trends in a nutshell. The red line (measured on the right-hand axis) shows that the average age of the global poulation was about 27 years back in 1980, is now up to about 35 years ,and is headed above 40 years in a few decades. The blue line shows average annual population growth. From 1980 to the present, it fell from 1.8% to about 0.8%, and it’s headed toward negative population growth later this century.

Of cousre, this decline in population growth isn’t distributed equally. This figure shows the timing at which countries start to experience a decline in the “working-age” population, defined here as ages 15-64. As you can see, Germany, France, Italy, and Japan were already experiencing a declin in the working-age population before the year 2000. Since 2000, the US, Canada, China, Korea, and Brazil have joined the club. In the 2030s, India and Indonesia will start to experience a declining working-age population. By later in the century, the pattern is projected to reach countries across Africa, like Nigeria, Ethiopia, Kenya, Ghana, and others.

Does a decline in working-age population necessarily mean a corresponding decline in economic output? Maybe not. There will be more workers with greater experience. In addition, people seem to be maintaining their cognitive sharpness and physical health later in life, which is not only a good thing in and of itself, but also increases the chance that they will continue contributing to the economy as workers for a few years longer. The IMF rreport notes:

Alongside increases in longevity, the functional capacity of older individuals has improved over time. More recent cohorts of older individuals are physically stronger and cognitively abler than earlier cohorts at the same age. Notably, when cognitive capacities are the focus, “the 70s are the new 50s”: Data from a sample of 41 advanced and emerging market economies indicate that, on average, a person who was 70 in 2022 had the same cognitive ability as a 53-yearold in 2000. Over the course of a decade, this pace of improvement in cognitive abilities is associated with an increase of approximately 20 percentage points in the likelihood that individuals remain engaged in the labor market, either by working or actively seeking employment, along with an increase of about six hours in average weekly hours worked and a 30 percent rise in labor earnings, conditional on being employed.

Ultimately,the ability of economies to adjust to these demographic shifts will rely on a few variables: Is there at least a moderate upward trend in the number of people who continue working after age 65? Are people saving more, so that they will be ready for longer retirement? Will the skills of experienced older workers perhaps be an especially good complement with emerging AI tools, thus allowing them to maintain high productivity for longer? Are people planning for old age without too heavy a reliance on support from the smaller younger generations of their families? Is the private sector making the kind of investments in technology and physical capital that can raise the productivity of older workers? Will the public sector adjust old-age pensions to keep them solvent? Is a combination of the private and public sector making the kinds of investments so that homes, public spaces, and care facilities are available and accessible to an older population?

There’s an old line that “everybody talks about the weather, but nobody does anything about it.” One might say something similar about the monumental trend toward global aging. The IMF report sketches out a model of a future where various adjustments in labor force participation, technology, investment, and government policies helps smooth the transition to a “silver economy.” But in many countries, for many people, I suspect it will be a bumpy ride.

China’s economy is an unconventional mixture of central control and subsidies, especially involving the large state-owned firms and the financial sector, mixed with widespread use of privately owned firms and market mechanisms. One common mechanism has been to reward local government officials for meeting the goals that the central government has set for economic growth in their area. This arrangement can work reasonably well–right up to when it doesn’t.

Jeffery (Jinfan) Chang, Yuheng Wang, and Wei Xiong focus on this part of China’s economic story in “Taming Cycles: China’s Growth Targets and Macroeconomic Management” (Brookings Papers on Economic Activity, Spring 2025). Here’s their description of the process of economic goal-setting across levels of China’s government.

From provinces, directly beneath the central government, down to cities, counties, and townships, each level of local government plays a crucial role in translating national targets into concrete economic outcomes. At the start of each year, local governments set their own growth targets in coordination with higher authorities, drawing on assessments of local economic conditions. A notable feature of this process is the phenomenon of “top-down amplification”—whereby national growth targets are consistently exceeded by provincial targets, which in turn are surpassed by city-level targets. This pattern reflects the incentive structure of China’s governance system, where local officials are assessed based on their ability to implement directives from higher authorities and drive economic growth within their jurisdictions. Consequently, regional leaders often set ambitious growth targets that exceed the expectations of their superiors. This strategy serves a dual purpose: providing a buffer to ensure compliance with higher-level expectations while also
motivating subordinates to outperform expectations. In this context, growth targets function not merely as planning tools but as instruments that foster competition among local governments. Our findings reveal a ratchet effect in how local governments adjust their growth targets asymmetrically—raising them aggressively during economic booms but lowering them more cautiously during slowdowns.

This figure illustrates the process in action. The dotted blue line is the national growth rate target. The red solid line is actual growth. The yellow dashed line is the province-level growth target (weighted by economic size of the province) and the green dashed line is the city-level growth target (weighte by economic size of the city).

As the authors point out, it’s useful to think of this figure as in two parts. In the first part, up through about 2010, the target rate for China’s growth is high and the actual growth rate is well above the target. Provinces and cities could set aggressive growth targets accordingly. But after about 2010, the real growth rate drops down to the national target, and the target itself is gradually reduced. The province- and city-level targets also come down, but more slowly.

An unwelcome dynamic emerges here. In the first decade or so of the figure, China’s growth was booming in substantial part as a result of an export surge, following China’s entry into the World Trade Organization in 2001. Lower levels of government could compete with each other to facilitate this growth.

But consider the position of state and local governments as growth rates sag in the second part of the figure. Province- and city-level officials are being held responsible for meeting growth targets, and for them, the idea of proposing lower-level targes for growth is likely to sound dangerous. Many of them will look for ways to prop up the higher growth rates. The province- and city-level governments basically have two sources of funds to do this: land sales and borrowing. Indeed, one reason that China’s growth remained robust during the Great Recession of 2008 was that the central government gave lower levels of government permission to increase their borrowing–and in this way to stimulate their economies. The borrowed money was often used to build infrastructure, not necessarily because the infrastructure was needed, but just because the building itself counted as part of local economic growth for purposes of meeting the targets.

You can see where this is headed. The authors estimate that local-government debt, from 2011-19, grew by an amount equal to 14% of national GDP. The infrastructure that was built during this time was not reflected in greater revenue growth among publicly listed firms (which can be used as a proxy for the underlying economic growth beyond the government debt-induced sugar rush). The authors write:

The disconnect between GDP growth and broader economic indicators may stem from key mechanisms identified in studies of the Chinese economy. As infrastructure investment faced diminishing returns, large-scale projects likely failed to generate meaningful spillover effects (e.g., Qian, Ru, and Xiong, 2024). Meanwhile, the surge in local government debt crowded out capital that could have otherwise supported more productive private enterprises, hindering organic economic growth. This pattern aligns with findings from Cong and others (2019) and Huang, Pagano, and Panizza (2020) on the effects of China’s post-crisis stimulus.

To put it another way, local government officials under competitive pressure across areas to facilitate organic economic growth can be a useful development approach. But local government officials under competitive pressure to substitute for organic economic growth, by using debt to juice the local economy, will tend to leave behind a pile of questionable debt. Meanwhile, China’s official national growth targets were trending down, and how much to trust the official GDP statistics remains a very open question.